Online research in philosophy

Prospective memory is required for many aspects of everyday cognition, its breakdown may be as debilitating as impairments in retrospective memory, and yet, the former has received relatively little attention by memory researchers. This article outlines a strategy for changing the fortunes of prospective memory, for guiding new research to shore up the claim that prospective memory is a distinct aspect of cognition, and to obtain evidence for clear performance dissociations between prospective memory and other memory functions. We begin by identifying the unique requirements of prospective memory tasks and by dividing memory's prospective functions into subdomains that are analogous to divisions in retrospective memory (e.g., short- versus long-term memory). We focus on one prospective function, called prospective memory proper; we define this function in the spirit of James (1890) as requiring that we are aware of a plan, of which meanwhile we have not been thinking, with the additional consciousness that we made the plan earlier. We give an operational definition of prospective memory proper and specify how it differs from explicit and implicit retrospective memory and how it might be empirically assessed.

Aggleton & Brown (A&B) propose that the hippocampal-anterior thalamic and perirhinal-medial dorsal thalamic systems play independent roles in episodic memory, with the hippocampus supporting recollection-based memory and the perirhinal cortex, recognition memory. In this commentary we discuss whether there is experimental support for the A&B model from studies of long-term memory in semantic dementia.

1. Introduction: memory and interdisciplinarity (footnote 1) Memory is studied at a bewildering number of levels, in a daunting range of disciplines, and with a vast array of methods. Is there any sense at all in which memory theorists - from neurobiologists to narrative theorists, from the developmental to the postcolonial, from the computational to the cross-cultural - are studying the same phenomena? This exploratory review paper sketches the bare outline of a positive framework for understanding current work on memory, both within the various cognitive sciences and across the gulfs between the cognitive and the social sciences.

Introduction to complexity and complex systems -- Introduction to large linear systems -- Introduction to biochemical oscillators and nonlinear biochemical systems -- Modularity, redundancy, degeneracy, pleiotropy and robustness in complex biological systems -- The evolution of biological complexity; invertebrate immune systems -- Irreducible and specified complexity in living systems -- The complex adaptive and innate human immune systems -- Complexity in quasispecies : microRNAs -- Introduction to complexity in economic systems -- Complexity in quasispecies : micrornas -- Dealing with complexity.

Ruchkin et al. ascribe a pivotal role to long-term memory representations and binding within working memory. Here we focus on the interaction of working memory and long-term memory in supporting on-line representations of experience available to guide on-going processing, and we distinguish the role of frontal-lobe systems from what the hippocampus contributes to relational long-term memory binding.

Robert Rosen has proposed several characteristics to distinguish “simple” physical systems (or “mechanisms”) from “complex” systems, such as living systems, which he calls “organisms”. The Memory Evolutive Systems (MES) introduced by the authors in preceding papers are shown to provide a mathematical model, based on category theory, which satisfies his characteristics of organisms, in particular the merger of the Aristotelian causes. Moreover they identify the condition for the emergence of objects and systems of increasing complexity. As an application, the cognitive system of an animal is modeled by the “MES of cat-neurons” obtained by successive complexifications of his neural system, in which the emergence of higher order cognitive processes gives support to Mario Bunge’s “emergentist monism.”.

The limited capacity for unrelated things is a fact that needs to be explained by a general theory of memory, rather than being itself used as a means of explaining data. A pure storage capacity is therefore not the right assumption for memory research. Instead an explanation is needed of how capacity limitations arise from the interaction between the environment and the cognitive system. The ACT-R architecture, a theory without working memory but a long-term memory based on activation, may provide such an explanation.

A distinction between interpretive processing and post-interpretive processing calls for a consideration of interface relations in systems of verbal memory. Syntactic movement of a phrase and the cognitive system of thought/mind interact. Systems of declarative memory and procedural memory interact.

In the context of mechanistic explanation, reductionistic research pursues a decomposition of complex systems into their component parts and operations. Using research on circadian rhythms and memory consolidation as exemplars, we consider the gains to be made by finding genes and proteins that figure in mechanisms underlying behavioral phenomena. However, we also show that such research is insufficient to explain the initial phenomenon. Accordingly, researchers have increasingly recognized the need to consider higher-level organization and integration with other systems. This illustrates a common need to complement reductionistic inquiry with investigations at higher levels and identifies a trajectory whereby cognitive science can embrace molecular neuroscience without surrendering its own contributions.

Psychoneural reduction is under attack again, only this time from a former ally: cognitive neuroscience. It has become popular to think of the brain as a complex system whose theoretically important properties emerge from dynamic, non-linear interactions between its component parts. ``Emergence'' is supposed to replace reduction: the latter is thought to be incapable of explaining the brain qua complex system. Rather than engage this issue at the level of theories of reduction versus theories of emergence, I here emphasize a role that reductionism plays – and will continue to play – even if neuroscience adopts this ``complex systems'' view. In detailed investigations into the function of complex neural circuits, certain questions can only be addressed by moving down levels and scales. This role for reduction also finds a place for approaches that dominate mainstream neuroscience, like the widespread use of experimental techniques and theories from molecular biology and biochemistry. These are difficult to reconcile with the anti-reductionist sentiments of the ``complex systems'' branch of cognitive neuroscience.